CLL clonal evolution and the development of therapy-driven resistance

CLL 克隆进化和治疗驱动耐药性的发展

基本信息

批准号：
10005158
负责人：
Catherine Ju-Ying Wu
金额：
$ 36.08万
依托单位：
DANA-FARBER CANCER INST
依托单位国家：
美国
项目类别：
财政年份：
2016
资助国家：
美国
起止时间：
2016-09-01 至 2021-09-16
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10005158
关键词：
Address Agammaglobulinaemia tyrosine kinase Animals B-Lymphocytes BCL2 gene Blood CRISPR/Cas technology Cell Line Cells Cessation of life Chronic Lymphocytic Leukemia Clinical Clinical Management Clinical Trials Clonal Evolution Clustered Regularly Interspaced Short Palindromic Repeats Combination Drug Therapy Cyclophosphamide DNA sequencing Data Data Set Death Rate Detection Development Disease Disease Progression Dissection Epigenetic Process Evolution Exposure to Genetic Genetic Heterogeneity Genome Genomics Genotype Goals Growth Immunodeficient Mouse Immunotherapy In Vitro Individual Kinetics Knowledge Lesion Leukemic Cell Malignant - descriptor Malignant Neoplasms Maps Mature B-Lymphocyte Measurement Measures Methods Modeling Molecular Mus Mutate Mutation Nature Pathway interactions Patient-Focused Outcomes Patients Pattern Phenotype Population Process Receptor Signaling Receptors, Antigen, B-Cell Relapse Resistance Resistance development Sampling Series Signal Transduction Specimen System Technology Testing Therapeutic Therapeutic Agents Time anti-PD1 antibodies base cancer cell cancer heterogeneity cancer therapy chemotherapy cohort curative treatments design droplet sequencing exome fitness fludarabine genetic profiling genome editing genome-wide genomic locus improved in vivo in vivo Model individual patient inhibitor/antagonist leukemia mathematical model next generation sequencing novel novel therapeutics personalized medicine phenome resistance gene resistance mechanism resistance mutation response rituximab standard of care success targeted agent therapy development therapy resistant tool transcriptome sequencing treatment response

项目摘要

Project Summary The ability of cancer cells to evolve and adapt to therapy is a challenge that limits treatment success and durability of responses. This is certainly the case in chronic lymphocytic leukemia (CLL), a malignancy of mature B cells that remains incurable, despite the potent cytolytic effects of both existing standard-of-care fludarabine-based combination chemotherapy, and newly developed targeted inhibitors such as ibrutinib and ABT199. We focus on a series of informative well-characterized clinical cohorts of patients that have relapsed following CLL therapy, ranging from conventional chemotherapy to novel agents (ibrutinib, ABT199, anti-PD1 antibody). Through integrated whole-exome and RNA-sequencing of these cohorts, we will characterize the extent of clonal evolution following exposure to these agents, and identify if there are consistent genetic loci associated with therapeutic resistance or progression (Aim 1). Mathematical modeling together with frequent serial analysis of the clonal composition of leukemias in relationship to treatment response and relapse can inform us regarding the clone-specific decline/growth kinetics as they occur in individual patients, and thereby enable dissection of the mechanisms of relapse or progression. Through this process, we will further estimate the sizes of clones with rare resistance mutations at the start of treatment; understand whether distinct relapse- associated genetic lesions result in accelerated clonal growth, or rather, in insensitivity to therapy; and validate the size of the resistant population in the starting population using novel single cell droplet sequencing technology (Aim 2). Finally, we will use CRISPR/Cas technology to model the novel resistance mutations in B cell lines and introduce these lines in combination with other mutated cell lines both in vitro and in vivo into immunodeficient mice, in order to test their fitness both prior to and during therapy (Aim 3). Altogether, the proposed analyses serve to provide an analytic framework for gaining vital information regarding the fitness of different genetic lesions with and without therapy, which may be immensely beneficial to the design of the next generation of therapeutic approaches to overcome the evolutionary capacity of cancer.

项目概要癌细胞进化和适应治疗的能力是一个挑战，限制了治疗的成功和响应的持久性。慢性淋巴细胞白血病 (CLL) 就是这种情况，这是一种恶性肿瘤尽管现有的标准治疗具有强大的细胞溶解作用，但成熟的 B 细胞仍然无法治愈以氟达拉滨为基础的联合化疗，以及新开发的靶向抑制剂，如依鲁替尼和 ABT199。我们专注于一系列信息丰富、特征明确的复发患者临床队列 CLL 治疗后，从传统化疗到新型药物（依鲁替尼、ABT199、抗 PD1 抗体）。通过对这些队列进行整合的全外显子组和 RNA 测序，我们将表征暴露于这些物质后克隆进化的程度，并确定是否存在一致的遗传位点与治疗耐药或进展相关（目标 1）。数学建模与频繁对白血病克隆组成与治疗反应和复发之间关系的系列分析可以告诉我们有关个体患者中发生的克隆特异性衰退/生长动力学的信息，从而能够剖析复发或进展的机制。通过这个过程，我们将进一步估计治疗开始时具有罕见耐药突变的克隆的大小；了解是否明显复发- 相关的基因损伤导致克隆生长加速，或者更确切地说，导致对治疗不敏感；并验证使用新型单细胞液滴测序确定起始群体中耐药群体的大小技术（目标 2）。最后，我们将利用 CRISPR/Cas 技术对 B 中的新型抗性突变进行建模细胞系，并将这些细胞系与体外和体内的其他突变细胞系结合引入免疫缺陷小鼠，以测试其在治疗前和治疗期间的健康状况（目标 3）。总而言之，拟议的分析旨在提供一个分析框架，用于获取有关健康状况的重要信息有或没有治疗的不同基因损伤，这可能对下一步的设计非常有益克服癌症进化能力的治疗方法的产生。